On Spectral Partitioning of Co-authorship Networks

Abstract : Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we explore two community detection approaches based on the spectral partitioning to analyze a co-authorship network. The partitioning exploits the concepts of algebraic connectivity and characteristic valuation to form components useful for the analysis of relations and communities in real world social networks.
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Communication dans un congrès
Agostino Cortesi; Nabendu Chaki; Khalid Saeed; Sławomir Wierzchoń. 11th International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2012, Venice, Italy. Springer, Lecture Notes in Computer Science, LNCS-7564, pp.302-313, 2012, Computer Information Systems and Industrial Management. 〈10.1007/978-3-642-33260-9_26〉
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Václav Snášel, Pavel Krömer, Jan Platoš, Miloš Kudělka, Zdeněk Horák. On Spectral Partitioning of Co-authorship Networks. Agostino Cortesi; Nabendu Chaki; Khalid Saeed; Sławomir Wierzchoń. 11th International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2012, Venice, Italy. Springer, Lecture Notes in Computer Science, LNCS-7564, pp.302-313, 2012, Computer Information Systems and Industrial Management. 〈10.1007/978-3-642-33260-9_26〉. 〈hal-01551743〉

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